Job Description
As an AI/ML Engineer, you will be part of Operation Center, India (INOPC-PG), aiming to develop a global value chain, where key business activities, resources, and expertise are shared across geographic boundaries to optimize value for Hitachi Energy customers across markets. As part of Transformers BU, we provide high-quality engineering and Technology to Hitachi Energy world. This is an important step from Hitachi Energy’s Global Footprint strategy.
How you’ll Make an Impact:
- Develop and support end‑to‑end AI/ML pipelines for transformer design, operations, manufacturing, and service-related workflows, including data ingestion, model training, evaluation, and deployment.
- Assist in architecting cloud-based AI/ML and GenAI resources (compute, storage, AI services) based on solution requirements and use cases.
- Build and integrate Generative AI solutions such as LLM-based assistants, retrieval‑augmented generation (RAG) systems, and domain‑specific chatbots for engineering and operational users.
- Support the development of agentic AI workflows, where AI agents can reason, plan, and coordinate tasks across tools, data sources, and systems under defined guardrails.
- Co‑develop AI solutions in a collaborative, cross‑functional environment, working closely with transformer design engineers, operations teams, and digital product stakeholders.
- Help translate engineering and operational requirements into technical solution designs and modular AI architectures.
- Support the implementation of MLOps and GenAIOps practices, including automation, versioning, monitoring, and lifecycle management.
- Contribute to testing, validation, and performance tuning of AI/ML and GenAI solutions prior to deployment.
- Document solution designs, AI architectures, and pipeline workflows to support scalability and reuse across functions.
- Participate in design reviews, technical discussions, and continuous learning initiatives related to applied AI in the transformer domain.
Your Background:
- Bachelor’s (B.E / B.Tech) or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related field.
- Hands‑on experience (academic, internship, or early professional) building AI/ML pipelines.
- Strong experience managing and configuring build agents (including self-hosted environments)
- Proficiency in Python, including ML and data libraries (e.g., scikit‑learn, TensorFlow/PyTorch, NumPy, Pandas).
- Exposure to Generative AI concepts, including large language models (LLMs), embeddings, prompt engineering, or RAG-based systems.
- Familiarity with agent‑based or multi‑step AI workflows (e.g., tool calling, orchestration, reasoning loops) at a conceptual or prototype level.
- Basic experience with cloud platforms (preferably Microsoft Azure) and AI/ML services.
- Experience working with structured and semi‑structured data using SQL databases and/or cloud storage.
- Understanding of core ML concepts, model evaluation, and responsible AI practices.
- Ability to collaborate effectively in a team-oriented, co‑development setup with engineers and domain experts.
- Strong analytical skills, clear communication, and a willingness to learn new technologies.
Preferred
- Experience with Azure ML, Azure AI Studio, Databricks, or similar platforms.
- Familiarity with LLM frameworks (e.g., Semantic Kernel, LangChain, or equivalents).
- Exposure to CI/CD, containerization, or MLOps/GenAIOps concepts.
- Basic understanding of engineering or industrial systems workflows (design, manufacturing, operations, or service).
